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Head and Neck Pathology Mar 2019
Topics: Color; Humans; Mouth Diseases; Mouth Mucosa; Pathology, Clinical
PubMed: 30693461
DOI: 10.1007/s12105-019-01007-3 -
Archives of Pathology & Laboratory... Oct 2021Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology...
CONTEXT.—
Recent developments in machine learning have stimulated intense interest in software that may augment or replace human experts. Machine learning may impact pathology practice by offering new capabilities in analysis, interpretation, and outcomes prediction using images and other data. The principles of operation and management of machine learning systems are unfamiliar to pathologists, who anticipate a need for additional education to be effective as expert users and managers of the new tools.
OBJECTIVE.—
To provide a background on machine learning for practicing pathologists, including an overview of algorithms, model development, and performance evaluation; to examine the current status of machine learning in pathology and consider possible roles and requirements for pathologists in local deployment and management of machine learning systems; and to highlight existing challenges and gaps in deployment methodology and regulation.
DATA SOURCES.—
Sources include the biomedical and engineering literature, white papers from professional organizations, government reports, electronic resources, and authors' experience in machine learning. References were chosen when possible for accessibility to practicing pathologists without specialized training in mathematics, statistics, or software development.
CONCLUSIONS.—
Machine learning offers an array of techniques that in recent published results show substantial promise. Data suggest that human experts working with machine learning tools outperform humans or machines separately, but the optimal form for this combination in pathology has not been established. Significant questions related to the generalizability of machine learning systems, local site verification, and performance monitoring remain to be resolved before a consensus on best practices and a regulatory environment can be established.
Topics: Algorithms; Artificial Intelligence; Female; Humans; Machine Learning; Male; Neural Networks, Computer; Pathologists; Pathology
PubMed: 33493264
DOI: 10.5858/arpa.2020-0541-CP -
Hormones & Cancer Dec 2011The ability to measure steroid hormone concentrations in blood and urine specimens is central to the diagnosis and proper treatment of adrenal diseases. The traditional... (Review)
Review
The ability to measure steroid hormone concentrations in blood and urine specimens is central to the diagnosis and proper treatment of adrenal diseases. The traditional approach has been to assay each steroid hormone, precursor, or metabolite using individual aliquots of serum, each with a separate immunoassay. For complex diseases, such as congenital adrenal hyperplasia and adrenocortical cancer, in which the assay of several steroids is essential for management, this approach is time consuming and costly, in addition to using large amounts of serum. Gas chromatography/mass spectrometry profiling of steroid metabolites in urine has been employed for many years but only in a small number of specialized laboratories and suffers from slow throughput. The advent of commercial high-performance liquid chromatography instruments coupled to tandem mass spectrometers offers the potential for medium- to high-throughput profiling of serum steroids using small quantities of sample. Here, we review the physical principles of mass spectrometry, the instrumentation used for these techniques, the terminology used in this field and applications to steroid analysis.
Topics: Adrenal Cortex Hormones; Adrenal Gland Diseases; Animals; Chromatography, Gas; Chromatography, High Pressure Liquid; High-Throughput Screening Assays; Humans; Mass Spectrometry; Pathology, Molecular
PubMed: 22170384
DOI: 10.1007/s12672-011-0099-x -
Folia Histochemica Et Cytobiologica Jan 2009The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic... (Review)
Review
The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous education in anatomy and pathology. First attempts to introduce them into routine work have been reported. Application of AI has been established by automated immunohistochemical measurement systems (EAMUS, www.diagnomX.eu). The performance of automated diagnosis has been reported for a broad variety of organs at sensitivity and specificity levels >85%). The implementation of a complete connected AI supported system is in its childhood. Application of AI in digital tissue--based diagnosis will allow the pathologists to work as supervisors and no longer as primary "water carriers". Its accurate use will give them the time needed to concentrating on difficult cases for the benefit of their patients.
Topics: Artificial Intelligence; Diagnosis, Computer-Assisted; Humans; Image Processing, Computer-Assisted; Immunohistochemistry; Pathology
PubMed: 20164018
DOI: 10.2478/v10042-009-0087-y -
Archiwum Medycyny Sadowej I Kryminologii 2014Clinical practice has an effective methodology of diagnostic procedures to be followed in cases of sepsis. However, there are as yet no corresponding standards of action... (Review)
Review
Clinical practice has an effective methodology of diagnostic procedures to be followed in cases of sepsis. However, there are as yet no corresponding standards of action in post-mortem diagnostics. The scope of examinations is limited to an autopsy and histopathological tests. This situation may lead to errors in medico-legal opinions on the cause of death and in the assessment of appropriateness of medical procedures. In cases of suspected sepsis, medico-legal investigations require obtaining detailed information about the circumstances of death (including symptoms and results of intravital examinations) before autopsy is performed, as well as sterile collection of specimens for microbiological tests and interpretation of their results on the basis of knowledge of epidemiology, pathophysiology and clinical progression of sepsis.
Topics: Autopsy; Biomarkers; Cause of Death; Death Certificates; Forensic Pathology; Humans; Postmortem Changes; Sepsis
PubMed: 25909922
DOI: 10.5114/amsik.2014.50532 -
Archives of Pathology & Laboratory... Jun 2024Although the basic principles of intraoperative diagnosis in surgical neuropathology have not changed in the last century, the last several decades have seen dramatic... (Review)
Review
CONTEXT.—
Although the basic principles of intraoperative diagnosis in surgical neuropathology have not changed in the last century, the last several decades have seen dramatic changes in tumor classification, terminology, molecular classification, and modalities used for intraoperative diagnosis. As many neuropathologic intraoperative diagnoses are performed by general surgical pathologists, awareness of these recent changes is important for the most accurate intraoperative diagnosis.
OBJECTIVE.—
To describe recent changes in the practice of intraoperative surgical neuropathology, with an emphasis on new entities, tumor classification, and anticipated ancillary tests, including molecular testing.
DATA SOURCES.—
The sources for this review include the fifth edition of the World Health Organization Classification of Tumours of the Central Nervous System, primary literature on intraoperative diagnosis and newly described tumor entities, and the authors' clinical experience.
CONCLUSIONS.—
A significant majority of neuropathologic diagnoses require ancillary testing, including molecular analysis, for appropriate classification. Therefore, the primary goal for any neurosurgical intraoperative diagnosis is the identification of diagnostic tissue and the preservation of the appropriate tissue for molecular testing. The intraoperative pathologist should seek to place a tumor in the most accurate diagnostic category possible, but specific diagnosis at the time of an intraoperative diagnosis is often not possible. Many entities have seen adjustments to grading criteria, including the incorporation of molecular features into grading. Awareness of these changes can help to avoid overgrading or undergrading at the time of intraoperative evaluation.
Topics: Humans; Neuropathology; Intraoperative Period; Pathology, Surgical; Central Nervous System Neoplasms
PubMed: 37694565
DOI: 10.5858/arpa.2023-0097-RA -
Biochemia Medica Feb 2017The External Quality Assessment (EQA) in Brazil is performed by the National Health Ministry for diseases that are under supervision of Public Health Department. In... (Review)
Review
The External Quality Assessment (EQA) in Brazil is performed by the National Health Ministry for diseases that are under supervision of Public Health Department. In addition to the government program, the Brazilian Society of Clinical Analysis and the Brazilian Society of Medical Pathology are allowed to provide their programs under the Supervision of National Agency for Sanitary Surveillance (ANVISA) that regulates laboratories to perform EQA programs.
Topics: Brazil; Clinical Laboratory Techniques; Humans; Medical Laboratory Science; Pathology, Clinical; Quality Assurance, Health Care; Quality Control
PubMed: 28392731
DOI: 10.11613/BM.2017.012 -
Applied Clinical Informatics Apr 2018Failure of timely test result follow-up has consequences including delayed diagnosis and treatment, added costs, and potential patient harm. Closed-loop communication is...
BACKGROUND
Failure of timely test result follow-up has consequences including delayed diagnosis and treatment, added costs, and potential patient harm. Closed-loop communication is key to ensure clinically significant test results (CSTRs) are acknowledged and acted upon appropriately. A previous implementation of the Alert Notification of Critical Results (ANCR) system to facilitate closed-loop communication of imaging CSTRs yielded improved communication of critical radiology results and enhanced adherence to institutional CSTR policies.
OBJECTIVE
This article extends the ANCR application to pathology and evaluates its impact on closed-loop communication of new malignancies, a common and important type of pathology CSTR.
MATERIALS AND METHODS
This Institutional Review Board-approved study was performed at a 150-bed community, academically affiliated hospital. ANCR was adapted for pathology CSTRs. Natural language processing was used on 30,774 pathology reports 13 months pre- and 13 months postintervention, identifying 5,595 reports with malignancies. Electronic health records were reviewed for documented acknowledgment for a random sample of reports. Percent of reports with documented acknowledgment within 15 days assessed institutional policy adherence. Time to acknowledgment was compared pre- versus postintervention and postintervention with and without ANCR alerts. Pathologists were surveyed regarding ANCR use and satisfaction.
RESULTS
Acknowledgment within 15 days was documented for 98 of 107 (91.6%) pre- and 89 of 103 (86.4%) postintervention reports ( = 0.2294). Median time to acknowledgment was 7 days (interquartile range [IQR], 3, 11) preintervention and 6 days (IQR, 2, 10) postintervention ( = 0.5083). Postintervention, median time to acknowledgment was 2 days (IQR, 1, 6) for reports with ANCR alerts versus 6 days (IQR, 2.75, 9) for reports without alerts ( = 0.0351). ANCR alerts were sent on 15 of 103 (15%) postintervention reports. All pathologists reported that the ANCR system positively impacted their workflow; 75% (three-fourths) felt that the ANCR system improved efficiency of communicating CSTRs.
CONCLUSION
ANCR expansion to facilitate closed-loop communication of pathology CSTRs was favorably perceived and associated with significant improved time to documented acknowledgment for new malignancies. The rate of adherence to institutional policy did not improve.
Topics: Automation; Communication; Documentation; Female; Humans; Laboratory Critical Values; Male; Middle Aged; Natural Language Processing; Pathology
PubMed: 29874687
DOI: 10.1055/s-0038-1654700 -
AIDS (London, England) Jun 2020: Rapid autopsy at the end of life in people with HIV (PWH) permits the preservation of valuable tissue specimens for subsequent study of HIV reservoirs. At our...
: Rapid autopsy at the end of life in people with HIV (PWH) permits the preservation of valuable tissue specimens for subsequent study of HIV reservoirs. At our institution, we have developed a cohort of PWH who consent to a rapid autopsy to gather a wide range of fluids and tissues with the goal of advancing HIV cure research. The protocol for successfully performing these autopsies has required careful thought and development over months and years. We have now successfully performed six rapid autopsies and detail here our steps to build the study cohort, train and staff a team of more than a dozen personnel, and process and preserve hundreds of samples from each autopsy.
Topics: Altruism; Autopsy; Cohort Studies; Forensic Pathology; HIV Infections; Humans; Tissue and Organ Procurement
PubMed: 32287073
DOI: 10.1097/QAD.0000000000002546 -
Archives of Pathology & Laboratory... Apr 2021Smart glasses are a wearable technology that enable hands-free data acquisition and entry.
CONTEXT.—
Smart glasses are a wearable technology that enable hands-free data acquisition and entry.
OBJECTIVE.—
To develop a surgical pathology grossing application on a smart glass platform.
DESIGN.—
An existing logistics software for the Google Glass Enterprise smart glass platform was used to create surgical pathology grossing protocols. The 2 grossing protocols were developed to simulate grossing a complex (heart) and a simple (kidney) specimen. For both protocols, users were visually prompted by the smart glass device to perform each task, record measurements, or document the field of view. In addition to measuring the total time of the protocol performance, each substep within the protocol was automatically recorded. Subsequently, a report was generated that contained the dictation, images, voice recordings, and the timing of each step. The application was tested by 3 users using the 2 grossing protocols. The users were tracked across 3 grossing procedures for each protocol.
RESULTS.—
For the complex specimen grossing the average time across repeated procedures was not significantly different between users (P > .99). However, when grossing times of the complex specimen were compared for repeated performances of the same user, a significant reduction in grossing times was observed with each repetition (P = .002). For the simple specimen, the average grossing time across multiple attempts was different among users (P = .03); however, no improvement in grossing time was observed with repeated performance (P = .499).
CONCLUSIONS.—
Augmented reality based grossing applications can provide automated data collection to track the changes in grossing performance over time.
Topics: Animals; Automation, Laboratory; Clinical Laboratory Techniques; Data Collection; Dissection; Humans; Kidney; Mobile Applications; Myocardium; Pathology, Surgical; Proof of Concept Study; Reminder Systems; Sheep, Domestic; Smart Glasses; Software Design; Specimen Handling; Time Factors; User-Computer Interface; Workflow
PubMed: 32823276
DOI: 10.5858/arpa.2020-0090-OA